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All Journal Journal of Food and Pharmaceutical Science Jurnal Pendidikan Matematika Undiksha Scan : Jurnal Teknologi Informasi dan Komunikasi Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer Akta Kimia Indonesia WIDYABHAKTI Jurnal Ilmiah Populer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Networks, Architecture and High Performance Computing JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Tika JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Emasains : Jurnal Edukasi Matematika dan Sains Prioritas : Jurnal Pengabdian Kepada Masyarakat Dharma Jnana Jurnal Ilmiah Ilmu Terapan Universitas Jambi Jurnal Pengabdian Kepada Masyarakat Widya Mahadi Journal of Global Pharma Technology Jurnal Kendali Teknik dan Sains Journal of Food and Pharmaceutical Sciences Jurnal Media Akademik (JMA) Jurnal Bisnis Inovatif dan Digital Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Fusion : Journal of Research in Engineering, Technology and Applied Sciences Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Saturnus: Jurnal Teknologi dan Sistem Informasi KOMET Router : Jurnal Teknik Informatika dan Terapan
I WAYAN SUDIARSA
STMIK STIKOM Indonesia
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Perancangan Sistem Antisipasi Terhadap Luapan Air Pada Selokan Berbasis Internet Of Things Jepri Martana, I Nyoman; Sudiarsa, I Wayan; Dirgayusari, Ayu Manik; Adnyana, I Gede
Jurnal Tika Vol 7 No 2 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v7i2.1319

Abstract

The impact of overflowing water in this ditch is the emergence of many diseases in the community and of course activities will be hampered. Because the possibility of flooding caused by overflow in the ditch, it is hoped that there will be a system that can reduce or even prevent flooding in areas that are prone to flooding due to overflowing sewers. As is the case with the problem at one location in Petak Kelod Village, precisely in Banjar Madangan Kaja, which experienced a problem in the gutter that almost every heavy rain came, causing the sewer to be clogged due to several factors such as: the size of the ditch is not the same which causes the water flow to become blocked, then the garbage in the gutter also causes the flowing water to become clogged. To overcome this, we need a system that can drain the blocked water flow by flowing it towards a larger ditch so as to make the clogged sewer smoother. The systems used to support this research are Arduino Uno, NodeMCU ESP8266, Ultrasonic Sensors, LEDs, and Stepper Motors, where the system will send the water level status via telegram and open the door automatically if the water level threshold is reached to be channeled to the backup channel so that the water is divided into two with the same volume and causes the waterway to return to normal. In the Esp8266 NodeMCU Connection Testing test, 100% success was obtained with an error of 6.934% in ultrasonic sensor testing, overall system performance was measured and 100% success was obtained
Implementation of Sibi Sign Language Realtime Detection Program (Case Studi At Sekolah Luar Biasa Negeri 1 Tabanan) Suyitno, Yoga Kristian; Sudiarsa, I Wayan; Hartawan, I Nyoman Buda; Putra, I Dewa Putu Gede Wiyata
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4405

Abstract

Indonesian deaf people utilize SIBI to communicate using spoken words, gestures, facial expressions, and body language. SIBI, certified for Special Schools (SLB), helps deaf pupils communicate. This project implements SIBI (Indonesian Sign Language System) a real-time detection algorithm at Sekolah Luar Biasa Negeri 1 Tabanan using image processing and YoloV8 ultralytics deep learning. The program trains a sign language gesture detection model on Google Colab's GPU. The SIBI sign language images were used to train a YoloV8 object detection model. The camera captures movements, which the YoloV8 algorithm trained on SIBI gesture data processes. It can recognize gestures in real time and generate text to non-sign language users. The dataset has 107 class vocabulary and 7 class affix prefixes for complete gesture recognition. Shirt color, room brightness, and webcam quality affect detection rates. Optimal detection accuracy is 87.74% and subpar 58.02%. Despite these limitations, the strategy helps deaf students communicate more effectively with non-sign language speakers. This program improves inclusivity and communication in schools, making learning easier for hearing-impaired pupils. This work provides a reliable and quick sign language identification system to help deaf educators and caregivers with daily interactions and education.
PENINGKATAN PRODUKSI BAWANG MERAH PADA DESA BINAAN MELALUI INDIKATOR BISNIS TEKNOLOGI DI DESA SONGAN KECAMATAN KINTAMANI BANGLI I Made Suarta; Ida Ayu Agung Ekasriadi; I Wayan Sudiarsa
Jurnal Pengabdian Kepada Masyarakat Widya Mahadi Vol. 6 No. 1 (2025): Desember 2025
Publisher : LP3M Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59672/widyamahadi.v6i1.5806

Abstract

Songan B Village, Kintamani District, Bangli Regency, is a highland area with potential for horticultural agriculture, particularly shallots. However, local farmers face two main problems: high pest infestations (onion caterpillars, leaf miners, thrips, and groundworms) and post-harvest marketing constraints due to limited market access, promotional strategies, and product packaging. In response, the Indonesian PGRI Mahadewa University (Universitas PGRI Mahadewa Indonesia), through its Technology Business Incubator (IBT) program, is providing mentoring to the Giri Amerta I shallot farmer group. Community service activities were implemented using the Technology Business Indicator approach, which included outreach, training, application of appropriate technology, ongoing mentoring, evaluation, and sustainability planning. The program focused on three main aspects: environmentally friendly pest control using biopesticides, pest traps, and natural enemies; pest prevention through an integrated farming system; and increased marketing capacity through promotional strategies, branding, digital media utilization, and market networks. The results of the activities demonstrated increased knowledge and skills among farmers in cultivating high-yielding, environmentally friendly shallots, as well as a growing awareness of the importance of modern marketing strategies. Through collaboration between universities and the village community, this program is expected to increase shallot productivity and strengthen the competitiveness of farmers' products in Songan B Village.
PEMBUATAN MINYAK GOSOK BERBAHAN HERBAL VCO DAN JAHE Ni Made Sukma Sanjiwani; Ni Putu Ayu Mirah Mariati; Agung Ari Chandra Wibawa; I Wayan Surya Rahadi; Dewa Ayu Sri Handani; I Wayan Sudiarsa
Jurnal Pengabdian Kepada Masyarakat Widya Mahadi Vol. 6 No. 1 (2025): Desember 2025
Publisher : LP3M Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59672/widyamahadi.v6i1.5819

Abstract

The problems faced by the Abasan community are that both young and old people often experience muscle aches and pains and have low knowledge of the use of herbal rubbing oil, as well as low interest in making their own herbal rubbing oil. Based on these problems, the community service team provided solutions in the form of socialisation on the use of herbal rubbing oil and teaching the community how to make herbal rubbing oil. This community service method is based on three areas. First, the production area: conducting lectures and discussions on what partners need so that the production process of herbal rubbing oil can run normally. Second, the management area: teaching participants how to make herbal rubbing oil that is good for health. Third, the marketing field, which involves teaching participants how to sell massage oil products at affordable prices so that many people will buy them by making the packaging and labels attractive. This community service activity took place on Sunday, 1 June 2025, at the Rare Asrama Banjar Abasan Early Childhood Education Centre. The event was attended in person by residents of Banjar Abasan, Singapadu Tengah Village, Sukawati Sub-district, Gianyar Regency, Bali. During the socialisation phase, the speaker was Mrs Ni Made Sukma Sanjiwani, S.Si., M.Si. Mrs Sukma explained the use of herbal ginger and VCO massage oil for health purposes. During the demonstration stage, conducted by lecturers and students, the lecturer taught participants how to make herbal massage oil using VCO and ginger. The initial step involved blending the ginger, then mixing it with a small amount of VCO, stirring it, and squeezing it. The ginger pulp was then mixed with a small amount of VCO and squeezed again. The ginger extract obtained is then mixed with mint oil and eucalyptus oil, with additional VCO added until the calibration mark is reached. The lecturer also labels the herbal massage oil bottles with stickers to improve the packaging, which can be used as an example for participants to make and sell the oil themselves, potentially turning it into their own business
Implementasi Sistem Monitoring dan Kontrol Suhu Kelembaban Ruang Budidaya Jamur Berbasis IoT Manik Dirgayusari, Ayu; Sudiarsa, I Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 2 (2021): December
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.127

Abstract

Kondisi lingkungan lembab sangat dibutuhkan jamur tiram untuk hidup dengan baik. Di dalam memonitoring serta menjaga kondisi kelembaban pada ruang budidaya jamur tiram petani jamur tiram masih melakukannya dengan cara manual yaitu memeriksa kondisi kumbung dan menyemprotkan air secara langsung pada baglog dan ruang budidaya jamur tiram ketika kondisi cuaca sedang panas atau kelembaban kurang dari batas yang telah ditentukan. Kegiatan tersebut mengharuskan pembudidaya sering bolak-balik ke tempat budidaya jamur guna melakukan pengecekan berulang terhadap keadaan ruang pembudidayaan jamur. Pada penelitian ini dibuat sebuah sistem untuk memonitoring serta mengontrol suhu kelembaban pada ruang pembudidayaan jamur tiram. Pada sistem yang telah dibuat menggunakan sensor DHT22 untuk mengukur suhu dan kelembaban pada ruang budidaya, hasil pengukuran akan ditampilkan melalui layar LCD 20x4 secara offline serta melalui aplikasi blynk pada smartphone. Ketika kondisi kelembaban salah satu sensor lebih kecil dari setpoint yang telah di inputkan pada keypad 4x3, maka akan ada pesan notifikasi dan relay akan menghidupkan pompa nozzle kabut. Kemudian ketika kelembaban pada ruang budidaya lebih besar dari setpoint maka pompa akan mati.
Analisis Tren Gaji Profesi AI di Pasar Kerja Global Tahun 2025 Berdasarkan Data Lowongan Pekerjaan Ni Putu Kania Mahadina; I Wayan Sudiarsa; Ni Putu Sri Indah Wulandari; Putu Paramita Rusaldi
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1403

Abstract

Rapid developments in the Artificial Intelligence (AI) industry have triggered an increased need for workers with specialized competencies, which has implications for significant variations in salary levels. This research aims to analyze the factors that influence salaries in the AI sector using the multiple linear regression method. The dataset used includes 15,000 AI job vacancies with variables including job and company characteristics. The data was engineered via the one-hot encoding method and divided into two parts: training data (80%) and test data (20%). The analysis results show that the regression model is able to explain 85% of the variation in salary, with an R² value of 0.85 and a Root Mean Square Error (RMSE) of USD 23,221. The three main factors identified as having a significant influence on salaries in the AI field are work experience, company location, and the industry in which the company operates. The experience factor reflects the skills and knowledge developed over many years, which can increase productivity (Rony et al., 2023). Company location also plays an important role, as the cost of living and demand for skilled labor varies by region (Badran, 2019). Additionally, the specific industry in which an employee works influences salary, given that more developed industries can often offer higher compensation (Huang, 2025). This research makes a significant empirical contribution to the understanding of compensation structures in the AI labor market.
Analisis Prediksi Penjualan Bisnis Retail Menggunakan Metode Decision Tree dan Random Forest Agung Narayana Adhi Putra; I Wayan Sudiarsa; I Kadek Adi Gunawan; Kadek Bagus Karunia Dwi Dharmayasa; I Wayan Eka Saputra
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1409

Abstract

The retail industry generates an extremely large and continuously growing volume of transactional data along with the advancement of digital technology, thereby requiring sophisticated and systematic data analysis approaches to support effective and evidence-based business decision-making. This study aims to analyze retail sales data by utilizing the Retail Sales Dataset obtained from the Kaggle platform, which consists of 100,000 transaction records and broadly represents the characteristics of retail transactions. The main focus of this study is to classify product categories and predict customer segments, including the identification of high-spending customers (high spenders), based on demographic attributes such as age and gender, as well as various transaction-related features. The research methodology includes data preprocessing, label encoding, and feature engineering to generate additional variables, including Age_Group, Is_Holiday, and Spender_Group, which are expected to enhance the predictive capability of the models. Several machine learning algorithms, namely Decision Tree, Random Forest, and XGBoost, were implemented and evaluated to compare their respective performance. The experimental results indicate that multiclass product category classification achieves relatively low accuracy, ranging from 27% to 34%. These findings suggest the high complexity of retail data and highlight the need for further model optimization, class balancing techniques, and feature refinement to improve predictive performance in future studies.
ANALISIS KLASIFIKASI PERILAKU PENGGUNA TERHADAP CUSTOMER CHURN PADA LAYANAN MUSIK SPOTIFY MENGGUNAKAN METODE RANDOM FOREST I Komang Dika Setiawan; I Wayan Sudiarsa; I Putu Diva Naratama; Aslin Thanelab Nope
Jurnal Media Akademik (JMA) Vol. 4 No. 1 (2026): JURNAL MEDIA AKADEMIK Edisi Januari
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/qcrcst95

Abstract

Perkembangan platform streaming musik digital seperti Spotify telah meningkatkan persaingan antar platform, sehingga perusahaan harus lebih berkonsentrasi pada strategi untuk mempertahankan pelanggan. Customer churn, atau keadaan di mana pelanggan berhenti menggunakan layanan, adalah salah satu masalah utama yang dihadapi. Tingkat churn yang tinggi dapat mengganggu keberlanjutan dan pendapatan perusahaan. Tujuan dari penelitian ini adalah untuk melihat bagaimana perilaku pengguna berdampak pada churn pelanggan pada layanan musik Spotify. Selain itu, penelitian ini juga akan mengevaluasi kemampuan metode Random Forest dalam klasifikasi churn. Metode kuantitatif bersama dengan metode data mining digunakan dalam penelitian ini. Dataset yang digunakan dibuat menggunakan Kaggle dan terdiri dari 8.000 data pengguna yang memiliki dua belas atribut, termasuk karakteristik pengguna, perilaku penggunaan, dan status churn. Penelitian melibatkan eksplorasi dan pra-pemrosesan data, pembagian data latihan dan uji, pengaturan hyperparameter, dan pembuatan model Random Forest. Hasil penelitian menunjukkan bahwa model Random Forest memiliki akurasi sebesar 74,12%, tetapi karena ketidakseimbangan data, dia memiliki nilai recall yang sangat rendah untuk kelas churn. Waktu mendengarkan, jumlah lagu yang diputar setiap hari, tingkat skip, usia, dan jumlah iklan yang didengarkan setiap minggu adalah faktor paling berpengaruh terhadap churn, menurut analisis fitur penting. Temuan ini menunjukkan bahwa pengalaman dan keterlibatan pengguna sangat penting dalam mempertahankan pelanggan. Hasil penelitian diharapkan dapat membantu penyedia layanan streaming musik membuat cara yang lebih baik untuk mempertahankan pelanggan mereka.
ANALISIS PERILAKU KONSUMEN DAN PREDIKSI PRODUK TERLARIS PADA BISNIS VENDING MACHINE MENGGUNAKAN ALGORITMA DECISION TREE I Gusti Ngurah Agung Putra Wijaya; I Wayan Sudiarsa; I Gusti Made Aditya Putra; I Kadek Yukiarta Putra; Augreselia Novita Nuer
Jurnal Media Akademik (JMA) Vol. 4 No. 1 (2026): JURNAL MEDIA AKADEMIK Edisi Januari
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/61as3004

Abstract

Perkembangan teknologi digital dan sistem otomatisasi mendorong transformasi signifikan dalam bisnis ritel, salah satunya melalui pemanfaatan vending machine yang terintegrasi dengan sistem pembayaran dan pencatatan transaksi digital. Data transaksi yang dihasilkan vending machine menyimpan potensi besar untuk dianalisis guna memahami perilaku konsumen dan memprediksi produk terlaris secara lebih akurat. Penelitian ini bertujuan untuk menganalisis perilaku konsumen serta memprediksi produk terlaris pada bisnis vending machine menggunakan algoritma Decision Tree. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan teknik data mining dan machine learning berbasis supervised learning. Dataset yang digunakan terdiri dari 9.617 data transaksi vending machine dengan 18 atribut yang mencakup informasi produk, harga, lokasi, waktu transaksi, dan metode pembayaran. Data diproses melalui tahapan eksplorasi data, pra-pemrosesan, pembangunan model, dan evaluasi kinerja. Hasil penelitian menunjukkan bahwa algoritma Decision Tree mampu menghasilkan kinerja prediksi yang cukup baik dengan nilai akurasi sebesar 76,30%, presisi 84,56%, recall 80,92%, dan F1-score 82,70%. Analisis feature importance mengungkapkan bahwa kategori produk, lokasi mesin, total nilai transaksi, dan harga produk merupakan faktor dominan dalam menentukan status produk terlaris. Temuan ini mengindikasikan bahwa pendekatan berbasis data dapat membantu pengelola vending machine dalam pengambilan keputusan terkait penyediaan stok, penempatan produk, dan strategi penjualan. Penelitian ini diharapkan memberikan kontribusi teoretis dalam kajian perilaku konsumen dan data mining serta implikasi praktis bagi pengembangan bisnis vending machine berbasis analitik data.
Implementasi Algoritma Random Forest untuk Klasifikasi Rentang Harga Ponsel Berdasarkan Spesifikasi Teknis Yustinus Liguori; I Wayan Sudiarsa; I Made Jagat Dita; I Gusti Ngurah Galih Jimbar Baskara; Pande Wisnu Wijaya Putra
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 4 (2025): Desember : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i4.796

Abstract

The rapid development of smartphone technology today creates challenges for consumers and manufacturers in determining an objective price range based on highly varied technical specifications. This study aims to implement the Random Forest algorithm in classifying smartphone price ranges into four main categories, namely low, mid-range, high, and flagship. The research method was carried out systematically through the stages of loading a dataset of 2,000 entries, exploratory data analysis (EDA) to ensure data integrity, and model training with a training and testing data split of 80:20. The results showed that the Random Forest model achieved a significant overall accuracy rate of 89%. Based on feature importance analysis, it was found that RAM capacity was the most dominant determining factor, contributing 47% to prediction accuracy, followed by battery power and screen resolution as supporting features. These findings have strategic implications for manufacturers to prioritize memory capacity upgrades in determining product pricing in the market, as well as providing guidance for consumers in assessing the fairness of a device's price based on its technical capabilities.
Co-Authors A. A. Gde Ekayana Agung Ari Chandra Wibawa Agung Narayana Adhi Putra Andika, I Gede Aniek Suryanti Kusuma, Aniek Suryanti Ariana, Anak Agung Gede Bagus Ariani, Komang Aslin Thanelab Nope Augreselia Novita Nuer Brian Adi Sapurta Dewa Ayu Ika Pramitha Dewa Ayu Putu Angelina Dewi Dewa Ayu Sri Handani Dewa Gde Agung Wisnu Anantha Dewa Putu Yudhi Ardiana Dirgayusari, Ayu Manik Gandika Supartha, I Kadek Dwi Gde Wardika Nugraha Gede Agus Santiago Giri, Putu Agus Semara Putra Gusti Ngurah Abhimanyu I Dewa Made Krishna Muku I Dewa Putu Juwana I Gede Adnyana I Gede Andika I Gede Iwan Sudipa I Gusti Ayu Anom I Gusti Made Aditya Putra I Gusti Ngurah Agung Putra Wijaya I Gusti Ngurah Galih Jimbar Baskara I Gusti Ngurah Rangga Mahesa I Kadek Adi Erawan I Kadek Adi Gunawan I Kadek Yukiarta Putra I Ketut Okta Suastika I Komang Dika Setiawan I Komang Hari Sastrawan I Komang Sukendra I Made Jagat Dita I Made Suarta I Made Suarta I Nyoman Agus Suarya Putra I Nyoman Buda Hartawan I P.Fajar Adi Pradipta I Putu Dicky Dharma Suryasa I Putu Diva Naratama I Putu Kabinawa Raesa Putra I Wayan Dharma Suryawan I Wayan Eka Saputra I Wayan Manik Mas Sri Dantya I Wayan Sumandya I Wayan Surya Rahadi Ida Ayu Agung Ekasriadi Indra Pratistha Jepri Martana, I Nyoman Kadek Bagus Karunia Dwi Dharmayasa Kadek Suryati Koda, Andrianus Koda, Moh M. Azmi Koda, Stanisilia D. Wero Made Hanindia Prami Swari Maharianingsih, Ni Made Maria Karlinda Maria Oktaviani Suryati Mitan, Maria M NI KADEK RINI PURWATI Ni Luh Putu Sandrya Dewi Ni Made Dwi Junita Sariyani Ni Made Lisma Martarini Ni Made Sukma Sanjiwani Ni Nyoman Padmawati Ni Nyoman Wahyu Udayani Ni Nyoman Yudianti Mendra Ni Putu Ayu Mirah Mariati NI PUTU AYU MIRAH MARIATI Ni Putu Kania Mahadina Ni Putu Sri Indah Wulandari Ni Wayan Karitha Pradnyandari Ni Wayan Sunita Pande Wisnu Wijaya Putra Pande, Ni Kadek Nita Noviani Pramana, I Made Wisnu Yoga Puguh Santoso Putra , I Dewa Putu Gede Wiyata Putra, I Made Agus Sunadi Putri Maria Theresia Kehi Putu Agus Aditya Putra Putu Paramita Rusaldi PUTU SUGIARTAWAN Rahadi, I Wayan Surya Sanjiwani, Ni Made Sukma Sanjiwani, Ni Made Sukma Sanjiwani Sastaparamitha, Ni Nyoman Ayu J. Satwika, I Kadek Susila Setya Cahyani, I Gusti Ayu Agung Dwita Socatama, I Putu Yoga Suradana, I Made Suyitno, Yoga Kristian Syamsiar, Syamsiar Tebai, Elisabeth Lydia Wardani, Ni Wayan Wayan Surya Rahadi Willdahlia, Ayu Gede Wiyata Putra, I Dewa Putu Gede Yosefina Dehadi Yulianus Kevin Dharmawa Sagur Yustinus Liguori Yuvensia Armelia Sumu Zamzak , M.Arif